feat: ✨ simple example for structured output (#100)

* feat: simple example for structured output

* feat: add documentation

Author: philippart-s

ai/ai-endpoints/README.md

@@ -15,6 +15,7 @@ Don't hesitate to use the source code and give us feedback.
 
 ### ☕️ Java demos ☕️
 
+  - [Simple Structured Output](./structured-output-langchain4j/)
   - [Natural Language Processing](./java-nlp)
   - [Chatbot with LangChain4j](./java-langchain4j-chatbot/): blocking mode, streaming mode and RAG mode.
   - [Blocking chatbot](./quarkus-langchain4j/) with LangChain4j and Quarkus

ai/ai-endpoints/structured-output-langchain4j/README.md

@@ -0,0 +1,16 @@
+# Simple structured output with LangChain4j and AI Endpoints
+
+### 🧰 Pre requisites 🧰
+
+  - Java 21+ installed (with preview mode enabled)
+  - AI Endpoints API token
+  - model to use: any of the LLM instruct models
+  - have the following environment variables created:
+    - OVH_AI_ENDPOINTS_ACCESS_TOKEN: the API token, see [documentation](https://help.ovhcloud.com/csm/en-gb-public-cloud-ai-endpoints-getting-started?id=kb_article_view&sysparm_article=KB0065401#generating-your-first-api-access-key) to know how to generate it
+    - OVH_AI_ENDPOINTS_MODEL_URL: URL of the model, see [AI Endpoints website](https://endpoints.ai.cloud.ovh.net/) to know how to get it.
+    - OVH_AI_ENDPOINTS_MODEL_NAME: model name, see [AI Endpoints website](https://endpoints.ai.cloud.ovh.net/) to know how to get it.
+    - [JBang](https://www.jbang.dev/documentation/guide/latest/index.html) installed
+
+## How to use the project
+
+  - run `jbang SimpleStructuredOutput.java` command

ai/ai-endpoints/structured-output-langchain4j/SimpleStructuredOutput.java

@@ -0,0 +1,62 @@
+///usr/bin/env jbang "$0" "$@" ; exit $?
+//JAVA 21+
+//PREVIEW
+//DEPS dev.langchain4j:langchain4j:1.0.1 dev.langchain4j:langchain4j-mistral-ai:1.0.1-beta6
+
+import com.fasterxml.jackson.databind.ObjectMapper;
+import dev.langchain4j.data.message.UserMessage;
+import dev.langchain4j.model.chat.request.ChatRequest;
+import dev.langchain4j.model.chat.request.ResponseFormat;
+import dev.langchain4j.model.chat.request.ResponseFormatType;
+import dev.langchain4j.model.chat.request.json.JsonObjectSchema;
+import dev.langchain4j.model.chat.request.json.JsonSchema;
+import dev.langchain4j.model.chat.response.ChatResponse;
+import dev.langchain4j.model.mistralai.MistralAiChatModel;
+import dev.langchain4j.model.chat.ChatModel;
+
+Person(String name, int age, double height, boolean married) {
+}
+
+void main() throws Exception {
+    ResponseFormat responseFormat = ResponseFormat.builder()
+            .type(ResponseFormatType.JSON)
+            .jsonSchema(JsonSchema.builder()
+                    .name("Person")
+                    .rootElement(JsonObjectSchema.builder()
+                            .addStringProperty("name")
+                            .addIntegerProperty("age")
+                            .addNumberProperty("height")
+                            .addBooleanProperty("married")
+                            .required("name", "age", "height", "married")
+                            .build())
+                    .build())
+            .build();
+
+    UserMessage userMessage = UserMessage.from("""
+            John is 42 years old.
+            He stands 1.75 meters tall.
+            Currently unmarried.
+            """);
+
+    ChatRequest chatRequest = ChatRequest.builder()
+            .responseFormat(responseFormat)
+            .messages(userMessage)
+            .build();
+
+    ChatModel chatModel = MistralAiChatModel.builder()
+            .apiKey(System.getenv("OVH_AI_ENDPOINTS_ACCESS_TOKEN"))
+            .baseUrl(System.getenv("OVH_AI_ENDPOINTS_MODEL_URL"))
+            .modelName(System.getenv("OVH_AI_ENDPOINTS_MODEL_NAME"))
+            .logRequests(false)
+            .logResponses(false)
+            .build();
+
+    ChatResponse chatResponse = chatModel.chat(chatRequest);
+
+    System.out.println("Prompt: \n" + userMessage.singleText());
+    String output = chatResponse.aiMessage().text();
+    System.out.println("Response: \n" + output); // {"name":"John","age":42,"height":1.75,"married":false}
+
+    Person person = new ObjectMapper().readValue(output, Person.class);
+    System.out.println(person); // Person[name=John, age=42, height=1.75, married=false]
+}